Modeling fecundity in the presence of a sterile fraction using a semi-parametric transformation model for grouped survival data.

The analysis of fecundity data is challenging and requires consideration of both highly timed and interrelated biologic processes in the context of essential behaviors such as sexual intercourse during the fertile window. Understanding human fecundity is further complicated by presence of a sterile population, i.e. couples unable to achieve pregnancy. Modeling techniques conducted to date have largely relied upon discrete time-to-pregnancy survival or day-specific probability models to estimate the determinants of time-to-pregnancy or acute effects, respectively. We developed a class of semi-parametric grouped transformation cure models that capture day-level variates purported to affect the cycle-level hazards of conception and, possibly, sterility. Our model's performance is assessed using simulation and longitudinal data from one of the few prospective cohort studies with preconception enrollment of women followed for 12 menstrual cycles at risk for pregnancy.